MCP server exposing Stockholm SL transit as AI agent tools — every response tagged with realtime / cached / stale_fallback / scheduled_fallback so the agent always knows how fresh its data is.
npx skills add devon1910/GTFS-Realtime-Transit-MCP-ServerMCP server exposing Stockholm SL transit as AI agent tools — every response tagged with realtime / cached / stale_fallback / scheduled_fallback so the agent always knows how fresh its data is.
Source: https://github.com/devon1910/GTFS-Realtime-Transit-MCP-Server
Discovered from GitHub repositories pushed in the last 24 hours for agent skills, Claude/Codex/Gemini workflows, MCP tooling, and adjacent AI-agent automation.
Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Automate web crawling and data extraction with Firecrawl -- scrape pages, crawl sites, extract structured data, batch scrape URLs, and map website structures through the Composio Firecrawl integration.
Detect & Counter Pickup Artist Tactics 2026 – AI-Powered Social Defense Toolkit
Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics.
Compare AdaL and Claude Code on Autoresearch benchmarks to find better hyperparameters, run more experiments, and converge faster